Project Summary A key goal of modern-day medicine is to use our knowledge of the unique genetic makeup of an individual patient to make personalized therapeutic decisions. For chronic lymphocytic leukemia (CLL), the advances in our knowledge of its disease genetics as well as the adoption of novel therapeutic agents in clinical practice have been rapid over recent years. Thus, the need now is ever more urgent to match patients with the appropriate therapeutic choice. Given the wealth of available human genetic data in CLL and our understanding of its genetic heterogeneity, our vision is that the path to precision medicine can be trail-blazed with CLL. Critical to this vision is the development of faithful animal models, since these would undoubtedly accelerate the preclinical testing of agents against genetically-defined subgroups. Herein, we propose leveraging the entirety of CLL genomics data, including genetic to methylation studies, to rationally create mouse models that provide the full range of genetic variability in order to recapitulate the clinical variability of patients. This goal is implementable because we recently demonstrated that the combined expression of 2 putative CLL driver events, identified from unbiased sequencing of patient samples, generates CLL-like disease that is highly faithful to the human disease. Specifically, co-expression of mutated Sf3b1 with Atm deletion (significantly associated together in patient samples) resulted in the development of clonal pathognomonic CD19+CD5+ B cells in blood, marrow and spleen at low penetrance in aged (18 months) mice, that can be propagated by in vivo passaging. With this work as a foundation, we now propose to investigate the hypothesis that distinct evolutionary paths are undertaken in CLL depending on the starting points of disease and that specific combinations of genetic events function to initiate malignancy, while others are critical for disease acceleration and even oncogenic transformation. To achieve this goal, we propose to leverage recently available facile genome-editing approaches, and a robust workflow we optimized to genetically manipulate mature B cells through engraftment of genome-edited B cell progenitor cells, in order to nimbly screen the functional impact of a variety of candidate driver mutations within a B cell context in vivo. We aim to identify the stepwise events required to initiate disease from normal B cells to a state of indolent malignancy (Aim 1), from indolent malignancy to more progressive disease (Aim 2), and even to aggressive lymphoma transformation (Aim 3). Generating such animal models is expected to provide an invaluable resource which will enable deep understanding of the functional impact of driver alterations, to accelerate disease prognostication, to facilitate rational evaluation of novel and combinatorial therapeutics, and to dissect the interaction of CLL cells with their in vivo microenvironment. Thus, we seek to create the same genetic heterogeneity in mice as in CLL patients so that we can faithfully model disease and provide a means to test therapeutics in advance?a stepping stone towards achieving precision medicine.